MA 05.03 - The Early Monitoring of Derived Neutrophil-To Lymphocyte Ratio (dNLR) Could Be a Surrogate Marker of Benefit of Immunotherapy in NSCLC (ID 10147)

Background: Baseline high derived NLR (dNLR>3, neutrophils/(leucocytes-neutrophils) ratio) has recently correlated with no benefit to immune checkpoint inhibitors (ICI) in advanced NSCLC, but the dynamic monitoring of dNLR has not been assessed in this population.

Method: dNLR at baseline, at 2[nd] cycle and at progressive disease were retrospectively collected in advanced NSCLC patients treated with ICI from November 2012 to April 2017, in a multicentric cohort (N= 292) from 4 European centers. The primary endpoint was overall survival (OS), and secondary endpoints were progression free survival (PFS), response rate (RR) and disease control rate (DCR).

Result: Out of 292 patients (67%) were males, 264 (92%) smokers and 239 (83%) with PS ≤1, with median age 64 years; 153 (52%) had adenocarcinoma and 114 (30%) squamous; 44 (15%) were KRASmut, 11 (4%) EGFRmut and 3 (1%) ALK positive. PDL1 was ≥ 1% by immunohistochemistry in 67 (76%), negative in 21 (24%) and unknown in 204 patients. The median of prior lines was 1 (0-10). The median follow-up was 12 months (m) [11-14]. The median PFS and OS were 4m [3-5] and 11m [9-15]. Baseline dNLR was>3 in 106 patients (36%) and at 2[nd] cycle in 90 patients (32%). dNLR>3 at baseline and at 2[nd] cycle were associated with poor PFS (p<0.0001 and p=0.0008, respectively), poor OS (both p<0.0001) and progressive disease (p=0.002 and p=0.005, respectively). At 2[nd] cycle of ICI, the dNLR status (> high or ≤ 3 low) changed in 63 patients: in 38 (14%) dNLR decreased; in 25 (9%) dNLR increased. According to the dNLR monitoring (combining dNLR at baseline et at 2[nd] cycle), the median OS was 17m (95%CI 13-NA) when dNLR remained low (n=153), 10m (95%CI 7-NA) when dNLR changed (n=64) and 4m (95%CI 3-7) when dNLR remained high (dNLR>3, n=64, p<0.0001).The dNLR monitoring was also associated with PFS (p=0.002), RR and DCR (p=0.003 and p=0.013, respectively).

Conclusion: Monitoring dNLR at baseline and at 2[nd] cycle could be a routinely tool to early assess benefit to ICI in NSCLC patients on treatment. The dNLR monitoring showed a strong correlation with OS and PFS. Modification of dNLR between baseline and 2[nd] cycle impacts outcomes in NSCLC patients treated with ICI.

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Background: Using Tumor Growth Rate (TGR), HPD was identified in 9% of 131 advanced cancer pts, treated with IO in a single institution (Champiat et al. 2017). In this study, we explored HPD in a large, multicenter cohort of advanced NSCLC pts treated with IO.

Method: We performed a retrospective analysis of consecutive NSCLC pts treated with IO, in 8 institutions, between November 2012 and April 2017. Eligibility criteria required, for each patient: 2 CT scans performed before starting IO and one during IO, an interval between two CT scans ≥2 weeks or 3 months (m) and presence of target lesions. CT scans were centrally assessed according to RECIST 1.1 criteria. We calculated TGR before IO (TGR pre-IO) and during IO (TGR IO); patients were defined HPD if they had progression disease (PD) at first evaluation during IO and a ≥ 2-fold increase in the TGR IO compared to TGR pre-IO. Median overall survival (mOS) was estimated using Kaplan-Meier method for the total population and HPD pts.

Conclusion: HPD occurred in 16% of advanced NSCLC pts treated with IO and was associated with plurimetastatic disease and appearance of new lung lesions. Further work is needed to characterize HPD prognostic value.

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Background: Platinum-based chemotherapy remains a first line treatment for advanced non-small-cell lung cancers (NSCLC). Despite better individualization of treatment, some patients will seek frequent medical attention because of cancer-related complications or treatment toxicity. This can negatively impact patient’s quality of life and health care resources. This study aimed to identify biological and clinical factors predictive of frailty and treatment toxicity among NSCLC patients eligible for first-line platinum-based chemotherapy.

Method: Using our institutional medical charts, we retrospectively extracted data on stage III and IV NSCLC patients diagnosed between December 2011 and November 2015 who had received a first-line platinum based chemotherapy. The primary outcome is defined as any unplanned emergency visit and/or unplanned hospitalization for cancer or treatment related complications. Using multivariate logistic regression model with step by step method, we defined baseline biological and clinical determinants associated with the primary outcome.

Result:

Table 1. First Multivariate Analysis

Variable

OR

95% CI

Age ≥ 62 Years-old

1.61

0.70 - 3.68

Adenocarcinoma - Squamous Cell Carcinoma - NSCLC other

1 2.43 0.50

0.61- 9.61 1.45 – 1.74

Performance scale ≥ 1

1.35

0.57 – 3.18

Number of metastasis ≥ 2

1.36

0.58 – 3.18

Pleural metastasis

2.04

0.53 – 7.86

Weight loss ≥10% or ≥3 kg

1.00

0.41 – 2.43

≥ 3 prescription drugs per day

0.98

0.42 – 2.28

Current smoker - Former Smoker - Never smoker

1 0.56 1.10

0.24 – 1.30 0.24 – 5.11

Neutrophils count ≥ 7500/ mm[3]

1.57

0.70 – 3.54

Lymphocytes count ≤ 1000/ mm[3]

1.04

0.34 – 3.22

Albumin ≤ 35 g/L

2.70

0.93 – 7.69

LDH ≥ 247 U/L

0.93

0.37 – 2.30

We included 227 patients. Mean age was 60 years old, 65% were male, 46% current smokers, 10% PS 2-3 and 74% had adenocarcinoma histology. 20,7% patients had locally advanced disease (Stage III) treated by chemoradiation and 78,4% had metastatic disease treated by exclusive chemotherapy. Median overall survival (OS) was 15 months and PFS 6 months. Overall, 55 % (122/227) met the primary outcome. There were 14 variables (Table 1) included in the first multivariate analysis before computer based step by step approach. In the final model (not shown), albumin level <35 g/L (OR 2.24 95% IC 1.14- 4.38, p= 0.02) was an independent predictor of the primary outcome. There was also a trend for squamous cell carcinoma subtype (OR 2.27 95% IC 0.872- 5.914, p= 0.09).

Conclusion: Low albumin level is a determinant of frailty in patients eligible for platinum-based chemotherapy. Early intervention in these subgroups could benefit patient’s quality of life and health care expenses. (Medicoeconomic analysis will be presented).

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Background: LIPI is a score that combine dNLR (neutrophils/(leucocytes-neutrophils) and lactate dehydrogenase (LDH) and correlate with prognosis of NSCLC patients treated with immune checkpoint inhibitors (ICI). We report the predictive role of LIPI on response and in various subgroups of patients.

Method: Baseline dNLR and LDH were retrospectively collected in 431 patients treated with ICI from Nov. 2012 to Jan. 2017, from 8 European centers. LIPI delineates 3 groups: good (dNLR<3+LDH3 or LDH>ULN), poor (dNLR>3+LDH>ULN). Response rate (RR) and disease control rate (DCR) were assessed according to the investigator’s criteria. The subgroup analysis was performed according to the age, histology, performance status (PS) and PD-L1 status by immunohistochemistry (positivity if ≥ 1% on tumor cells).

Result: With a median follow-up of 12.8 months (m.) [95%CI 11.9-14], 431 patients were included. Baseline characteristics are summarized in table 1. The median overall survival (OS) and progression-free survival (PFS) were 10.5m. [95%CI 9.5-13] and 3.9m. [3-4.4], respectively. The median OS was 4.8m. vs. 10 m. vs. 16.5m., and median PFS was 2m. vs. 3.1m. vs. 5m. for the poor, intermediate and good LIPI groups, respectively (both p<0.0001). LIPI was correlated with response rate (p<0.0001). In multivariate analysis, the intermediate and poor group were associated with progressive disease, with an OR of 2.20 [CI95% 1.26-3.84] p=0.005) and an OR of 3.04 [CI95% 1.46-6.36] p=0.003), respectively. LIPI was correlated with OS, regardless the age (<70 years (p<0.0001) vs. older (p=0.0006) and the histology non-squamous (p<0.0001) vs. squamous (p=0.02). In PS 0-1 and in smoker population, LIPI correlated with OS (both p<0.0001), but not in PS ≥2 (12%) and non-smokers (8%). LIPI was correlated with OS for positivity (p=0.01) and unknown PD-L1 (p=0.0001), but not negativity.

LIPI 0 Good (N=162, 37%)

LIPI 1 Intermediate (N=206, 48%)

LIPI 2 Poor (N= 63, 15%)

All population cohort N = 431 (%)

Sex

Male

102 (63)

131 (64)

42 (67)

275 (64)

Age at diagnosis

Median (years, range)

62 (36;86)

63 (29;86)

62 (39;84)

62 (29;86)

Smoking status

Non-smoker

13 (8)

18 (9)

5 (8)

36 (8)

Former

80 (49)

115 (56)

46 (73)

241 (56)

Current

67 (42)

69 (33)

11 (17)

147 (34)

Unknown

2

4

1

7

Histology

Non-squamous

111 (69)

132 (64)

41 (65)

284 (66)

Squamous

51 (31)

74 (36)

22 (35)

147 (34)

Molecular alteration

EGFR mutation

3 (2)

13 (6)

3 (5)

19 (4)

ALK rearrangement

2 (1)

2 (1)

1 (2)

5 (1)

KRAS mutation

34 (21)

31 (15)

8 (13)

73 (17)

PDL1 status

Negative

16 (36)

14 (25)

1 (5)

31 (25)

Positive

28 (64)

43 (75)

20 (95)

91 (75)

Unknown

118

149

42

337

Performance Status

0

51 (32)

45 (22)

10 (16)

106 (25)

1

96 (60)

132 (64)

42 (67)

270 (63)

≥ 2

12 (8)

28 (14)

11 (17)

51 (12)

Stage at diagnosis

IIIb

18 (11)

33 (16)

14 (22)

65 (15)

IV

101 (62)

135 (66)

38 (60)

274 (64)

Metastases sites

Median (Range)

2 (0;6)

2 (0;7)

2 (1;7)

2 (0-7)

Bone

43 (27)

58 (28)

20 (32)

121 (28)

Liver

28 (17)

39 (19)

16 (25)

83 (19)

Brain

22 (14)

19 (9)

9 (14)

50 (12)

Immunotherapy

PD1 inhibitor

133 (82)

167 (81)

48 (76)

348 (81)

PDL1 inhibitor

19 (12)

34 (17)

12 (19)

65 (15)

PDL1 inhibitor- CTLA4 inhibitor

10 (6)

5 (2)

3 (5)

18 (4)

Immunotherapy line

Median (Range)

2 (1;11)

2 (1;12)

2 (1;8)

2 (1-12)

Response rate

Complete response (CR)

6 (4)

3 (1)

0 (0)

8 (2)

Partial response (PR)

42 (26)

53 (26)

18 (28)

113 (26)

Stable disease (SD)

66 (41)

59 (29)

8 (13)

133 (31)

Progression

40 (25)

81 (39)

33 (52)

154 (36)

NA

8

10

4

25

Dissociated response

14 (9)

15 (7)

2 (3)

31 (7)

Conclusion: Baseline LIPI predicts response to ICI, and was correlated with OS regardless of age and histology.